excel reader mcp

Local 2025-08-31 23:22:06 0

Provides efficient handling of large Excel files through automatic chunking and pagination, using MCP to enable seamless file reading and management features such as sheet selection and error handling.


smithery badge A Model Context Protocol (MCP) server for reading Excel files with automatic chunking and pagination support. Built with SheetJS and TypeScript, this tool helps you handle large Excel files efficiently by automatically breaking them into manageable chunks.

Excel Reader MCP server

Features

  • ? Read Excel files (.xlsx, .xls) with automatic size limits
  • ? Automatic chunking for large datasets
  • ? Sheet selection and row pagination
  • ? Proper date handling
  • ⚡ Optimized for large files
  • ?️ Error handling and validation

Installation

Installing via Smithery

To install Excel Reader for Claude Desktop automatically via Smithery:

npx -y @smithery/cli install @ArchimedesCrypto/excel-reader-mcp-chunked --client claude

As an MCP Server

  1. Install globally:

    npm install -g @archimdescrypto/excel-reader

  2. Add to your MCP settings file (usually at ~/.config/claude/settings.json or equivalent):

    {
      "mcpServers": {
        "excel-reader": {
          "command": "excel-reader",
          "env": {}
        }
      }
    }

For Development

  1. Clone the repository:

    git clone https://github.com/ArchimdesCrypto/mcp-excel-reader.git
    cd mcp-excel-reader

  2. Install dependencies:

    npm install

  3. Build the project:

    npm run build

Usage

Usage

The Excel Reader provides a single tool read_excel with the following parameters:

interface ReadExcelArgs {
  filePath: string;      // Path to Excel file
  sheetName?: string;    // Optional sheet name (defaults to first sheet)
  startRow?: number;     // Optional starting row for pagination
  maxRows?: number;      // Optional maximum rows to read
}

// Response format
interface ExcelResponse {
  fileName: string;
  totalSheets: number;
  currentSheet: {
    name: string;
    totalRows: number;
    totalColumns: number;
    chunk: {
      rowStart: number;
      rowEnd: number;
      columns: string[];
      data: Record<string, any>[];
    };
    hasMore: boolean;
    nextChunk?: {
      rowStart: number;
      columns: string[];
    };
  };
}

Basic Usage

When used with Claude or another MCP-compatible AI:

Read the Excel file at path/to/file.xlsx

The AI will use the tool to read the file, automatically handling chunking for large files.

Features

  1. Automatic Chunking
  2. Automatically splits large files into manageable chunks
  3. Default chunk size of 100KB
  4. Provides metadata for pagination

  5. Sheet Selection

  6. Read specific sheets by name
  7. Defaults to first sheet if not specified

  8. Row Pagination

  9. Control which rows to read with startRow and maxRows
  10. Get next chunk information for continuous reading

  11. Error Handling

  12. Validates file existence and format
  13. Provides clear error messages
  14. Handles malformed Excel files gracefully

Extending with SheetJS Features

The Excel Reader is built on SheetJS and can be extended with its powerful features:

Available Extensions

  1. Formula Handling

    // Enable formula parsing
    const wb = XLSX.read(data, {
      cellFormula: true,
      cellNF: true
    });

  2. Cell Formatting

    // Access cell styles and formatting
    const styles = Object.keys(worksheet)
      .filter(key => key[0] !== '!')
      .map(key => ({
        cell: key,
        style: worksheet[key].s
      }));

  3. Data Validation

    // Access data validation rules
    const validation = worksheet['!dataValidation'];

  4. Sheet Features

  5. Merged Cells: worksheet['!merges']
  6. Hidden Rows/Columns: worksheet['!rows'], worksheet['!cols']
  7. Sheet Protection: worksheet['!protect']

For more features and detailed documentation, visit the SheetJS Documentation.

Contributing

  1. Fork the repository
  2. Create your feature branch (git checkout -b feature/amazing-feature)
  3. Commit your changes (git commit -m 'Add some amazing feature')
  4. Push to the branch (git push origin feature/amazing-feature)
  5. Open a Pull Request

License

This project is licensed under the MIT License - see the LICENSE file for details.

Acknowledgments

[
  {
    "description": "Read an Excel file and return its contents as structured data",
    "inputSchema": {
      "properties": {
        "filePath": {
          "description": "Path to the Excel file to read",
          "type": "string"
        },
        "maxRows": {
          "description": "Maximum number of rows to read (optional)",
          "type": "number"
        },
        "sheetName": {
          "description": "Name of the sheet to read (optional)",
          "type": "string"
        },
        "startRow": {
          "description": "Starting row index (optional)",
          "type": "number"
        }
      },
      "required": [
        "filePath"
      ],
      "type": "object"
    },
    "name": "read_excel"
  }
]